Data analytics can be used in multiple contexts. An example context can include predictive maintenance of devices. For example, data associated with a device can be analyzed to predict when and/or what type of maintenance may be needed to maintain acceptable operation of the device. Data analytics, however, can be resource intensive (e.g., in terms of technical resources such as processors, memory, bandwidth), and can require a relatively high skill level (e.g., data science and domain expert with engineering background) for review and action based on analytical results. These constraints can inhibit a broader use of data analytics.